Michael Chesnaye

A headshot of Michael Chesnaye

Auditory Evoked Potentials
Objective assessments of hearing
Signal processing
Statistics and machine learning

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Michael Chesnaye

Michael is a Biomedical Engineer with a background in Auditory Evoked Response (AER) detection methods. This primarily involves applying signal processing and statistical methods for estimating and/or detecting small changes in brain activity in response to sound. The main goal for this work is to assess the integrity and/or functioning of the auditory system, so that timely interventions can be carried out, and the cascade of adverse effects associated with untreated hearing loss prevented. From 2015 to 2023, Michael completed a PhD and two postdoctoral research positions in this area at the University of Southampton where he collaborated closely with Prof. Steven Bell and Prof. David Simpson. In 2024, he moved to Sydney where he is now working with Viji Easwar on (i) optimizing objective detection methods for speech-evoked responses, and (ii) identifying neural cues in infants with hearing loss to predict their speech and language outcomes later in life.


Postdoc fellow, University of Southampton (2019-2023)

PhD Biomedical Engineering, University of Southampton (2015-2019)

MSc Clinical Physics, University of Groningen (2012-2014)

Pre-MSc Biomedical Engineering, University of Groningen (2011-2012) BSc Artificial Intelligence, University of Groningen (2008-2011)


Chesnaye, M.A., Simpson, D.M., Schlittenlacher, J., & Bell, S.L. (2023). Hearing threshold estimation using Gaussian Processes and Auditory Brainstem Responses. IEEE Transactions on Biomedical Engineering.

Chesnaye, M.A., Bell, S.L., Harte, J.M., & Simpson, D.M. (2021). Controlling test specificity for auditory evoked response detection using a frequency domain bootstrap. Journal of Neuroscience Methods, 363, 109352. doi: 10.1016/j.jneumeth.2021.109352.

Chesnaye, M.A., Bell, S. L., Harte, J. M., & Simpson, D. M. (2019). A group sequential test for ABR detection. International Journal of Audiology, 58(10), 618-627. doi: 10.1080/14992027.2019.1625486.